Triple

T20838228
Position Surface form Disambiguated ID Type / Status
Subject Schutterwald E513018 entity
Predicate hasSubdivision P747 FINISHED
Object Müllen
Müllen is a small locality or district that forms part of the municipality of Schutterwald in the German state of Baden-Württemberg.
E1452536 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Müllen | Statement: [Schutterwald, hasSubdivision, Müllen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Müllen
Context triple: [Schutterwald, hasSubdivision, Müllen]
  • A. Mülligen
    Mülligen is a small Swiss municipality located in the canton of Aargau.
  • B. Mössinger
    Mössinger is a German surname most notably borne by Ingrid Mössinger, a prominent figure in the German art and museum world.
  • C. Mülbracht
    Mülbracht is a historical locality in the Holy Roman Empire known primarily as the birthplace of the Dutch Golden Age engraver and painter Hendrick Goltzius.
  • D. Muhr
    Muhr is a small Austrian municipality located in the mountainous Lungau region of the state of Salzburg.
  • E. Eckersmühlen
    Eckersmühlen is a village and district of the town of Roth in the Bavarian region of Germany.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Müllen
Triple: [Schutterwald, hasSubdivision, Müllen]
Generated description
Müllen is a small locality or district that forms part of the municipality of Schutterwald in the German state of Baden-Württemberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Müllen
Target entity description: Müllen is a small locality or district that forms part of the municipality of Schutterwald in the German state of Baden-Württemberg.
  • A. Mülligen
    Mülligen is a small Swiss municipality located in the canton of Aargau.
  • B. Mössinger
    Mössinger is a German surname most notably borne by Ingrid Mössinger, a prominent figure in the German art and museum world.
  • C. Mülbracht
    Mülbracht is a historical locality in the Holy Roman Empire known primarily as the birthplace of the Dutch Golden Age engraver and painter Hendrick Goltzius.
  • D. Muhr
    Muhr is a small Austrian municipality located in the mountainous Lungau region of the state of Salzburg.
  • E. Eckersmühlen
    Eckersmühlen is a village and district of the town of Roth in the Bavarian region of Germany.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0b4cf62a88190bbf92351e9e57259 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c32928788190be8ca57923eefd7e completed April 21, 2026, 12:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0900868558819099cf2668970a7f2c completed May 16, 2026, 11:40 p.m.
NEDg Description generation batch_6a0901a0dac081909f9184e99a70419a completed May 16, 2026, 11:45 p.m.
NED2 Entity disambiguation (via description) batch_6a09023cf27081908eb246367215ae12 completed May 16, 2026, 11:48 p.m.
Created at: April 16, 2026, 12:42 p.m.